Physical Sciences and Mathematics Commons^™

Bound Preserving Discontinuous Galerkin Methods For Euler Equations And Nonequilibrium Flows, Fangyao Zhu

Dissertations, Master's Theses and Master's Reports

This dissertation is composed of four chapters in which we will closely examine the high order bound preserving discontinuous Galerkin methods for solving partial differential equations, specifically non-equilibrium chemical reacting flows and Euler equations under gravitational fields. A shared requirement between the two is the necessity for positive values of both density and pressure. Due to this physical nature of the two systems, constructing a positivity preserving scheme become very essential in our research.

For non-equilibrium flows where multi-reactions and multi-species are involved, we are also required to keep the bounds of the mass fraction of each species in between …

Light Absorbing Aerosol Interactions With Warm Clouds, Shreya Joshi

Dissertations, Master's Theses and Master's Reports

Atmospheric particles such as biomass-burning aerosols, including black carbon - are critical in altering the Earth's energy balance through interactions with light and clouds. Biomass-burning aerosols also contain organic carbon, a diverse mix of organic compounds. As these aerosols age, they evolve by interacting with other atmospheric species, including cloud water, leading to changes in particle morphology and the development of coatings that impact their lifetime and ability to interact with clouds and light.

Some biomass-burning aerosols serve as cloud condensation nuclei. When cloud water droplets form, the properties of the nucleating particles can change. Many clouds evaporate before precipitating, …

Great Lakes And Its Regional Climate In The Future, Miraj Bhakta Kayastha

Dissertations, Master's Theses and Master's Reports

The overarching objective of this dissertation is to enhance our predictive understanding of the Great Lakes regional climate by utilizing advanced modeling techniques and provide comprehensive insights into the future of the Great Lakes. This dissertation focuses on four areas pertinent to the future of the Great Lakes hydroclimate and extreme events, beginning with the derivation of robust water level projections for the Great Lakes in Chapter 2. Using a regional climate modeling system with a two-way coupled three-dimensional (3D) hydrodynamic lake and ice model for the Great lakes, we analyze long-term future changes in the over-lake precipitation, lake evaporation, …

Hybrid Mixtures Of Factor Analyzers For High Dimensional Data, Kazeem Abiodun Kareem

Dissertations, Master's Theses and Master's Reports

Factor analysis is a powerful tool for modeling latent structures in high-dimensional data, traditional approaches assume a single global structure, limiting their ability to capture heterogeneity. The Mixture of Factor Analyzers (MFA) extends classical factor analysis by modeling data as a mixture of Gaussian-distributed local subspaces, effectively uncovering cluster-specific latent structures. However, MFA relies on Gaussian mixtures, making it sensitive to outliers and ill-suited for heavy-tailed data. The Mixture of $t$-Factor Analyzers (M$t$FA) addresses these limitations by incorporating multivariate $t$-distributions, improving robustness. Despite their advantages, both MFA and M$t$FA face significant computational challenges in high-dimensional settings, particularly due to costly …

Near-Infrared Fluorescent Cyanine Probes For Monitoring Nad(P)H Dynamics In Living Cells And Drosophila Larvae, May Waters

Dissertations, Master's Theses and Master's Reports

Nicotinamide adenine dinucleotide (NAD+/NADH) plays a critical role in cellular metabolism, with abnormally elevated NADH levels linked to disrupted metabolic processes and cancer. In this study, we developed near-infrared fluorescent probes to selectively measure NADH concentrations. We present five cyanine-based probes, which were optimized by modifying the connection bridges to fine tune electronics. Two NAD(P)H-biosensing probes consisting of 1,3,3-trimethyl-3H-indolium and 3-quinolinium acceptors, linked by thiophene, A, and 3,4-ethylenedioxythiophene, B, bridges are detailed. They exhibit near-infrared fluorescence at 742.1 nm and 727.2 nm for probes A and B, respectively, and generate absorbance signals at 690.6 nm and 685.9 nm. Probe A …

From Plasmonics To Superfluorescence: Engineering Light- Matter Interactions For Quantum Optical Phenomena, Aaron J. Wildenborg

Dissertations, Master's Theses and Master's Reports

This work presents different ways to engineer light-matter interactions by using nanostructures to exploit quantum-optical phenomena. First, sodium (Na) is predicted to be an ideal plasmonic material due to its ultra-low optical losses from the visible to the near-infrared (NIR). However, Na has practical limitations due to its high chemical reactivity. Using a scalable fabrication method for Na plasmonic nanostructures by combining phase-shift photolithography and a thermo-assisted spin-coating process, we produced nano-pit arrays of varying periodicities (300-600 nm), supporting tunable surface plasmon polariton (SPP) modes spanning visible to NIR. These structures demonstrated SPP resonances as narrow as 9.3 nm, with …

Kangaroo: Dynamic Fusion Of Branch Instructions In A Pipelined Uniprocessor, Sarah E. Larkin

Dissertations, Master's Theses and Master's Reports

Small pipelined processors are becoming more common as a complement to superscalars in a multi-core chip. However, current uniprocessors offer little in the way of ILP. We present kangaroo, a novel approach to instruction fusion in a pipelined processor. Kangaroo dynamically fuses two adjacent instructions to create a pair that travels through the pipeline as a unit. The instructions re-enter the pipeline as a pair the next time the first instruction is fetched. Unlike in prior art, an instruction, once fused, is not fetched again. Any pair of adjacent instructions can be fused using this technique, including dependent instructions. …

Utilizing Biometrics And Blockchain For Enhanced Security Of Remote Patient Monitoring (Rpm) Data Sharing, Amaturrahman Raihanah Medlock

Dissertations, Master's Theses and Master's Reports

Advancements in Artificial Intelligence (AI) and Internet of Medical Things (IoMT) technologies have significantly revolutionized the conventional healthcare systems. Through the integration of smart devices, medical sensors, and communication technology, IoMT provides real-time patient’s monitoring data for healthcare providers, thus promoting accurate and timely clinical decisions for patient-centric care. The current healthcare sector is evolving to a connected ecosystem with connectivity and intelligence. While it also incurs increasing security and privacy concerns as integrating IoMT generated patient monitoring data into healthcare information systems. Both blockchain and biometrics are measures that have established reputable names in the security realm. When evaluating …

Microwave Assisted Syntheses And Characterizations Of Near-Infrared Ratiometric Probes For Mitochondrial Ph Detection And Monitoring, Ronald J. Schwandt

Dissertations, Master's Theses and Master's Reports

Within the field of biochemistry, there has been a significant development of ratiometric fluorescent probes designed for mitochondrial pH detection; however, many of these probes have emissions within the visible spectrum and require long synthesis times with low-yield reactions. However, in recent years, microwave-assisted syntheses of organic molecules have led to significant increases in reaction yields and quicker reaction times. In this work, two common reactions in probe synthesis, Heck coupling, and Knoevenagel condensations are investigated using microwave-assisted synthesis. It was found the low-concentration Heck coupling reactions using palladium (II) acetate led to extremely efficient Heck coupling. Also, a novel …

Quantifying So₂ Emissions From Explosive Events Of The 2021 La Soufrière Eruption Using Dscovr/Epic, Yuxi Jin

Dissertations, Master's Theses and Master's Reports

Volcanic eruptions release large quantities of gases, including sulfur dioxide (SO₂), aerosol precursors, and ash into the atmosphere. Quantifying the emission fluxes and temporal variability of SO₂ is crucial for understanding volcanic processes and assessing their impacts on air quality, climate, and aviation safety. Episodic vulcanian to sub-Plinian explosive eruptions are a common feature of many arc volcanoes, but the underlying causes of such episodic behavior remain poorly understood. The 2021 La Soufrière eruption (St. Vincent) featured up to 40 discrete eruptive events between April 9 and April 22, presenting a rare opportunity to analyze time-resolved volcanic SO₂ emissions during …

Methods In Statistics, Machine Learning, And Deep Learning For Combining Multi-Omics Dataset, Md Mutasim Billah

Dissertations, Master's Theses and Master's Reports

Transcriptome-wide association studies (TWAS) have emerged as a powerful strategy to bridge genome-wide association studies (GWAS) with gene regulatory mechanisms by integrating genotypic data with gene expression data. While early TWAS methods typically rely on linear models and single-tissue expression references, recent advances underscore the need for flexible, multi-tissue approaches that can capture heterogeneous regulatory architectures and tissue-specific expression patterns. This dissertation introduces a three‑part research project that advances multi‑tissue transcriptome‑wide association studies (TWAS) along complementary axes of methodology, statistical power, and modelling flexibility.

In chapter One, TWAS‑CTL introduces a two‑stage cross‑tissue learner that trains any user‑chosen single‑tissue imputers (STLs) …

Generalizing Medical Image Segmentation Task With Efficient Deep Learning Models, Abel A. Reyes-Angulo

Dissertations, Master's Theses and Master's Reports

Medical Image Segmentation is a critical task in the field of medical imaging, playing a crucial role in diagnostics, treatment planning, and disease monitoring. The emergence of Deep Learning (DL) has ushered in a new era in Artificial Intelligence (AI), propelling remarkable advancements in key domains like language translation, object recognition, and recommendation systems. This evolution has been accompanied by continuous enhancements in computational efficiency and improvements in predictive accuracy. The introduction of sophisticated algorithms, such as convolutional neural networks (CNNs) and transformers, exemplifies these advancements. DL algorithms have demonstrated exceptional efficacy in medical image segmentation tasks, showcasing the potential …

Growth, Survival, And Herbivore Browsing Preferences Of Seedlings Planted In Black Ash Stands Of Northern Michigan And Wisconsin, Seth W. Davenport

Dissertations, Master's Theses and Master's Reports

To mitigate the cascading ecosystem impacts of widespread black ash (Fraxinus nigra) mortality due to the invasive emerald ash borer (Agrilus planipennis), forested wetlands can be underplanted with seedlings of alternative species that later repopulate the vacated canopy. This study examined the survival and growth, factors influencing performance, and herbivore browsing preferences of seven non-ash species planted in northern Michigan and Wisconsin. The best performing species were river birch (Betula nigra), silver maple (Acer saccharinum), and swamp white oak (Quercus bicolor). The worst performing species was black spruce (Picea …

Dam It All: A Multi-Scalar Investigation Into The Ecological Role And Function Of Beaver Dams, Kenneth Larsen

Dissertations, Master's Theses and Master's Reports

The central theme of this dissertation is ecological scaling, which examines how small, localized features, such as beaver ponds, contribute to large-scale watershed processes and how different modeling approaches at various scales reveal distinct insights. Through a combination of probabilistic modeling and high-resolution empirical research, this work demonstrates that small ponded systems, particularly those created by beavers (Castor canadensis), serve as critical biogeochemical control points, whose contributions to sediment and nutrient dynamics have been historically underestimated.

In Chapter 1, I contextualize this research within the broader fields of freshwater ecology, watershed modeling, and ecological restoration. I introduce the …

Three-Sided Skyline Counting Queries, Suruchi Kushwaha

Dissertations, Master's Theses and Master's Reports

A two-dimensional point p=(p.x,p.y) dominates another point p'=(p'.x,p'.y) if p.x ≥ p'.x and p.y>p'.y or p.x>p'.x and p.y ≥ p'.y. The skyline of a point set P is a subset P' ⊆ P such that every point in P' is not dominated by any other point in P. An orthogonal skyline counting query Q on a set of points P asks for the number of points on the skyline of P ⋂ Q.

In this work we study data structures that support orthogonal skyline counting queries in the special case when the query range is bounded on three …

Comprehensive Analysis Of Krauklis Waves And Long Period Seismic Events In Fluid-Filled Fractures Via Integrated Physical And Numerical Modeling, Sananda Ray

Dissertations, Master's Theses and Master's Reports

Long-period (LP) seismic events, commonly recorded in volcanic and hydrothermal environments, are widely attributed to the resonance of fluid-filled fractures and the excitation of Krauklis waves along the solid-fluid interface. These low-velocity, dispersive waves are sensitive to both fluid dynamics and fracture geometry, offering critical insights into subsurface fluid transport, fracture evolution, and seismic source processes. Despite robust theoretical treatments, experimental validation under realistic geological conditions has remained limited. To address this, I aimed to develop a series of laboratory-based experimental models that systematically investigate the key physical mechanisms driving LP signal generation. In the first set of experiments, I …

Multiscale Computational Chemistry Studies Of The Catalytic Mechanisms Of Non-Heme Fe(Ii)/2-Oxoglutarate-Dependent Oxygenases, Simahudeen Bathir Jaber Sathik Rifayee

Dissertations, Master's Theses and Master's Reports

Enzymes catalyze complex biological transformations. Non-heme Fe(II)/2-oxoglutarate (2OG)–dependent enzymes are highly versatile catalysts capable of selective C–H oxidation, enabling transformations such as hydroxylation, halogenation, desaturation, demethylation, ring rearrangements, epoxidation, and electrophilic aromatic substitution. These enzymes are involved in various biological processes, including fatty acid metabolism, hypoxic signaling, collagen maturation, and transcriptional regulation. Computational Modeling provides detailed knowledge of the enzymes including atomistic details of the important catalytic species, conformational and electronic effects, which are crucial to enzyme engineering and drug design efforts. This dissertation implements advanced multi-scale molecular modelling techniques including Molecular dynamics and Quantum Mechanic / Molecular Mechanics calculations …

Natural Capital Credit Risk Assessment In Agricultural Lending: An Approach Based On The Natural Capital Protocol, Francisco Ascui, Theodor Florian Cojoianu

Research Collection College of Integrative Studies

It is increasingly recognised that financial institutions have significant impacts and dependencies on natural capital – defined as the stock of the world’s renewable and non-renewable natural resources and ecosystems that yield flows of environmental goods and services, which directly and indirectly underpin the global economy and human wellbeing. Historically, many of these impacts and dependencies have been overlooked. The value of goods and services that nature provides ‘for free’ has often been ignored, and resources have typically been priced at their cost of extraction, rather than the cost of their replacement or substitution, which would promote more sustainable long-term …

Mapping The End Of Coal: How Policy Strength, Ownership, Finance Shape Global Plant Retirements, Jiwon Kim, Theodor Florian Cojoianu, Theodor F. Cojoianu, Maretno Agus Harjoto, Dariusz Wojcik

Research Collection College of Integrative Studies

This study examines how national environmental performance, institutional investor divestment from fossil fuels, investment in renewable energy, and ownership type influence the global phase-out of coal power plants, and whether these effects are constrained by geographical boundaries. Using data on coal plant retirements across 90 countries, we test whether domestic and cross-border factors shape the timing and likelihood of asset closure. We find that companies headquartered in countries with stronger environmental performance are more likely to retire domestic but not foreign plants. While institutional investors divestment is often assumed to exert cross-border influence, our findings show that divestment pressure by …

The Climate-Biodiversity-Pollution Nexus: The Pricing Of Environmental Credit Risks For European Industrial Polluters, Dominik Hirschbühl, Andrej Ceglar, Theodor Cojoianu, Tina Emambakhsh, Yifan Qi, Caterina Rho, Elsie Hu, Marco Petracco, Fabrizio Biganzoli, Alfred De Jager, Laura Garcia Herrero, Andrea Mandrici, Carlo Pasqua

Research Collection College of Integrative Studies

This study examines how euro area banks factor pollution-induced biodiversity risks into lending decisions, using data from 832 banks and 5,000 major polluters. Our results show that banks are increasingly pricing these risks by adjusting loan-to-value ratios and interest rates. Banks adjust lending conditions in line with EU pollution and biodiversity protection legislation, particularly for companies with large pollution footprints near biodiversity-protected areas or those contributing to Environmental Quality Standards failures of downstream surface waters. The former is driven primarily by banks’ adoption of biodiversity policies and public commitments to the Equator Principles, while the latter is a result of …

Meteorology, Weather And War In South East Asia: Malaya C. 1940-1960, Fiona Williamson

Research Collection College of Integrative Studies

This article interrogates the positioning of British colonial meteorology in Malaysia and Singapore from the 1940s to 1960. This period spanned a global conflict and an internecine war, effecting profound sociopolitical changes from which neither Malaysia nor Singapore would emerge the same. The meteorological services were essential to Britain's armed conflicts, providing vital weather information to the army, navy and, especially, the air forces, as well as supporting the aviation and shipping industry often in difficult and dangerous circumstances. This article argues that British military policy in South East Asia and the specific concerns of the colonial government in Malaya …

Your Cursor Reveals: On Analyzing Workers’ Browsing Behavior And Annotation Quality In Crowdsourcing Tasks, Pei-Chi Lo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this work, we investigate the connection between browsing behavior and task quality of crowdsourcing workers performing annotation tasks that require information judgements. Such information judgements are often required to derive ground truth answers to information retrieval queries. We explore the use of workers’ browsing behavior to directly determine their annotation result quality. We hypothesize user attention to be the main factor contributing to a worker’s annotation quality. To predict annotation quality at the task level, we model two aspects of task-specific user attention, also known as general and semantic user attentions . Both aspects of user attention can be …

The Gender Wage Gap In An Online Labor Market: The Cost Of Interruptions, Abi Adams, Kotaro Hara, Kristy Milland, Chris Callison-Burch

Research Collection School Of Computing and Information Systems

This paper analyses gender differences in working patterns and wages on Amazon Mechanical Turk, a popular online labour platform. Using information on 2 million tasks, we find no gender differences in task selection nor experience. Nonetheless, women earn 20% less per hour on average. Gender differences in working patterns are a significant driver of this wage gap. Women are more likely to interrupt their working time on the platform with consequences for their task completion speed. A follow-up survey shows that the gender differences in working patterns and hourly wages are concentrated amongst workers with children.

Development And Construction Of New Scanning Antennas With High Remote Sensing Capability For Wireless Communication Systems In The Millimeter Wavelength Range, Nagham Habeeb Shakir, Sarah R. Hashim, Ahmed Sileh Gifal, Ahmed Dheyaa Radhi, Alaa G.K. Alshami, Rusul Mansoor Alamri, Hussein Mohammed Ali

Mesopotamian Journal of Computer Science

In this paper, geometric methods and wave optics were used to calculate the basic profiles and characteristics of the lens antennas.  The planar reflector arrays were assembled using an iterative method with multiple forward and inverse Fourier transform calculations.  Three-dimensional electromagnetic modeling was performed in CST Microwave Studio software to evaluate the technical parameters of the designed antennas. Measurements of the characteristics of fabricated prototypes of far-field scanning antennas were performed using a custom-designed experimental setup. This study focuses on the analysis and development of scanning antennas for use in millimeter-wave wireless communication systems. The researchers aim to develop a …

Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

This chapter examines the difficult legal characterisation problems that artificially intelligent systems raise and explores how different characterisations of artificial intelligence (AI) shape practical legal outcomes. Three reasons are offered for the legal difficulty with characterising AI. First, answers to characterisation problems are inherently subjective and perspective-driven, particularly when the subject is an intangible technological system. Second, AI technology is especially difficult to define since the field typically proceeds on inexact anthropomorphic metaphors. Third, AI characterisation problems raise difficult sub-problems, particularly in determining how autonomous an AI system is. The chapter thus argues that a range of plausible AI characterisations …

Empowering Crisis Information Extraction Through Actionability Event Schemata And Domain-Adaptive Pre-Training, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

One of the persistent challenges in crisis detection is inferring actionable information to support emergency response. Existing methods focus on situational awareness but often lack actionable insights. This study proposes a holistic approach to implementing an actionability extraction system on social media, including requirement gathering, selection of machine learning tasks, data preparation, and integration with existing resources, providing guidance for governments, civil services, emergency workers, and researchers on supplementing existing channels with actionable information from social media. Our solution leverages an actionability schema and domain-adaptive pre-training, improving upon the state-of-the-art model by 5.5% and 10.1% in micro and macro F1 …

Risk Spillover Effect Of China-Asean Supply Chains: Insights Of Industrial Transfer, Zeyang Bian, Yuning Zhang, Keng Siau, Yaqian Zhang, Jianjia He

Research Collection School Of Computing and Information Systems

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of China and ASEAN but also reshapes the global manufacturing landscape. This paper investigates the correlation and spillover of supply chain risks using production exposure indicators derived from inter-country input-output data and the R-Vine Copula model. We assess the risk spillover of each country within the global supply chain. Our findings indicate that industrial relocation can significantly alter supply chain structures, thereby affecting the concentration and direction of risks. While China's role …

More Effective Javascript Breaking Change Detection Via Dynamic Object Relation Graph, Dezhen Kong, Jiakun Liu, Chao Ni, David Lo, Lingfeng Bao

Research Collection School Of Computing and Information Systems

JavaScript libraries are characterized by their widespread use, frequent code changes, and a high tolerance for backward incompatible changes. Awareness of such breaking changes can help developers adapt to version updates and avoid negative impacts. Several tools have been targeted to or can be used to detect breaking change detection in the JavaScript community. However, these tools detect breaking changes using different ways, and there are currently no systematic reviews of these approaches. From a preliminary study on popular JavaScript libraries, we find that existing approaches, including simple regression testing, model-based testing and type differencing cannot detect many breaking changes …

Defending Federated Recommender Systems Against Untargeted Attacks: A Contribution-Aware Robust Aggregation Scheme, Ruicheng Liang, Yuanchun Jiang, Feida Zhu, Ling Cheng, Huiwen Liu

Research Collection School Of Computing and Information Systems

Federated recommender systems (FedRSs) effectively tackle the tradeoff between recommendation accuracy and privacy preservation. However, recent studies have revealed severe vulnerabilities in FedRSs, particularly against untargeted attacks seeking to undermine their overall performance. Defense methods employed in traditional recommender systems are not applicable to FedRSs, and existing robust aggregation schemes for other federated learning-based applications have proven ineffective in FedRSs. Building on the observation that malicious clients contribute negatively to the training process, we design a novel contribution-aware robust aggregation scheme to defend FedRSs against untargeted attacks, named contribution-aware Bayesian knowledge distillation aggregation (ConDA), comprising two key components for the …

Label Correlated Contrastive Learning For Medical Report Generation, Xinyao Liu, Junchang Xin, Bing Tian Dai, Qi Shen, Zhihong Huang, Zhiqiong Wang

Research Collection School Of Computing and Information Systems

Background and Objective: Automatic generation of medical reports reduces both the burden on radiologists and the possibility of errors due to the inexperience of radiologists. The model that utilizes attention mechanism and contrastive learning can generate medical reports by capturing both general and specific semantics. However, existing contrastive learning methods ignore the specificity of medical data, that is, a patient may suffer from multiple diseases at the same time. This means that the lack of fine-grained relationships for contrastive learning will lead to the problem of insufficient specificity. Methods: To address the above problem, a label correlated contrastive learning method …